Acta Univ. Agric. Silvic. Mendelianae Brun. 2018, 66, 1325-1335

https://doi.org/10.11118/actaun201866051325
Published online 2018-10-29

Determinants of Commercial Banks’ Profitability. Evidence from Hungary

Isah Serwadda

Department of Finance, Faculty of Business and Economics, Mendel University, Zemědělská 1, 613 00 Brno, Czech Republic

This paper aims to find out whether bank‑specific (internal) factors impact on the profitability of commercial banks in Hungary for 16 a year period ranging from 2000–2015. The study employs a sample of twenty‑six commercial banks with four hundred sixteen observations. The study employs return on average assets (ROAA) as a proxy for bank profitability, and it also considers bank‑specific (internal) factors as independent variables. These include asset quality (non‑performing loans), overhead costs, bank size, net interest margin, and liquidity risk plus capital adequacy ratio. The study uses panel regressions, descriptive statistics and correlation analysis for the investigations. The panel regression models are to estimate the impact of bank‑specific (internal) factors on bank profitability. The Hausman specification test was conducted on the panel regression models in order to identify the best and appropriate model for the study. The empirical findings reveal that non‑performing loans, overhead costs and liquidity had a significant negative impact on bank profitability as bank size had a significant positive impact on profitability. However, net interest margin and capital adequacy ratio had no impact on bank profitability. The study concludes that bank size and asset quality are bank‑specific factors that have the biggest impact on commercial banks’ profitability in Hungary for the period under investigation. The study recommends that commercial banks should endeavor to manage and reduce overhead costs to be able to earn more profits since overhead costs adversely affect bank profitability. More so, commercial banks’ managers should regularly monitor credit and liquidity risk indicators as well as pursuing diversification policies of income sources while upholding optimisation of operational costs.

Funding

“This research was funded by Internal IGA project no. PEF_TP_2018006 at Mendel University, Faculty of Business and Economics”

References

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